In response to the demand of automatic fruit identification and harvesting,this paper presents a human-robot collaborative picking robot based on somatosensory interactive servo control.The robot system mainly consist...In response to the demand of automatic fruit identification and harvesting,this paper presents a human-robot collaborative picking robot based on somatosensory interactive servo control.The robot system mainly consisted of four parts:picking execution mechanism,hand information acquisition system,human-machine interaction interface,and human-robot collaborative picking strategy.A six-degree-of-freedom robotic arm was designed as the picking execution mechanism.The D-H method is employed for both forward and inverse kinematic modeling of the robotic arm.A four-step inverse kinematic optimal solution selection method,including mechanical interference,correctness,rationality,and smoothness of motion,is proposed.The working principle and use of the Leap Motion controller for hand information acquisition were introduced.Data from three types of hand movements were collected and analyzed.Spatial mapping method between the Leap Motion interaction space and operating range of the robotic arm was proposed to achieve a direct correspondence between the cubic interaction box and the cylindrical space of the fan ring of the robotic arm.The test results demonstrated that the average response time of the double-click picking command was 332 ms.The average time consumption for somatosensory control targeting was 6.5 s.The accuracy rate of the picking gesture judgment was 96.7%.展开更多
In greenhouse environments,using automated machines for tomato harvesting to reduce labor consumption is a future development trend.Accurate and effective visual recognition is essential to accomplish harvesting tasks...In greenhouse environments,using automated machines for tomato harvesting to reduce labor consumption is a future development trend.Accurate and effective visual recognition is essential to accomplish harvesting tasks.However,most current studies use various models to gain harvesting information in multiple steps,resulting in heavy calculation costs,poor real-time availability,and weak recognition precision.In this study,an improved YOLOv8np-RCW end-to-end model based on YOLOv8n pose is proposed to simultaneously detect tomato bunches,maturity,and keypoints using a decoupled-head structure.The model integrates a ResNet-enhanced RepVGG architecture for a balance of accuracy and speed,employs the CARAFE upsampling algorithm for a larger receptive field with lightweight design,and optimizes the loss function with WIoU loss to enhance bounding box prediction,maturity detection,and keypoint extraction.Experimental results indicate that mAP50 of YOLOv8np-RCW model for bounding box and keypoints is 87.3%and 86.8%respectively,which is 6.2%and 5.5%higher than YOLOv8n pose model.Completing the tasks of bunch detection,maturity assessment,and keypoint localization requires only 9.8 ms.Euclidean distance error is less than 20 pixels in detecting keypoints.Based on this model,a method is proposed to quickly determine the orientation of tomato bunches using geometric cross-product and cross-multiplication calculations from keypoint 2D information,providing guidance for the motion planning of the end-effector.In field experiments,the robot achieved a harvesting success rate of 68%,with an average time of 10.8366 seconds per tomato bunch.展开更多
In order to improve the operating precision of the harvesting robot,a vision system for intelligently identifying and locating the mature tomato was designed.The active detection method based on structured-light stere...In order to improve the operating precision of the harvesting robot,a vision system for intelligently identifying and locating the mature tomato was designed.The active detection method based on structured-light stereo vision was expected to deal with the problem of variable illumination and target occlusion in the glasshouse.The maximum between-cluster variances of hue(H)and saturation(S)value were adopted as the threshold for color segmentation,which weakened the impact on the image caused by the light intensity variation.Through the limit on the pixel size and circularity of the candidate areas,the vision system recognized the fruit area and removed the noise areas.The fruit’s 3D position was computed on the basis of spatial relationship between the laser plane and the camera,when the linear laser was projected on the centre area of the mature fruit.The blue view-scanning laser stripe pixels on the mature fruit were extracted according to its Cb color characteristic.As the field test results show,the measurement error on the fruit radius is less than 5 mm,the centre distance error between the fruit and camera is less than 7 mm,and the single axis coordinate error is less than 5.6 mm.This structured-light vision system could effectively identify and locate mature fruit.展开更多
With the decrease of agricultural labor and the increase of production cost,the researches on citrus harvesting robot(CHR)have received more and more attention in recent years.For the success of robotic harvesting and...With the decrease of agricultural labor and the increase of production cost,the researches on citrus harvesting robot(CHR)have received more and more attention in recent years.For the success of robotic harvesting and the safety of robot,the identification of mature citrus fruit and obstacle is the priority of robotic harvesting.In this work,a machine vision system,which consisted of a color CCD camera and a computer,was developed to achieve these tasks.Images of citrus trees were captured under sunny and cloudy conditions.Due to varying degrees of lightness and position randomness of fruits and branches,red,green,and blue values of objects in these images are changed dramatically.The traditional threshold segmentation is not efficient to solve these problems.Multi-class support vector machine(SVM),which succeeds by morphological operation,was used to simultaneously segment the fruits and branches in this study.The recognition rate of citrus fruit was 92.4%,and the branch of which diameter was more than 5 pixels,could be recognized.The results showed that the algorithm could be used to detect the fruits and branches for CHR.展开更多
In order to improve robotic harvesting and reduce production cost,a harvesting robot system for strawberry on the elevated-trough culture was designed.It was supposed to serve for sightseeing agriculture and technolog...In order to improve robotic harvesting and reduce production cost,a harvesting robot system for strawberry on the elevated-trough culture was designed.It was supposed to serve for sightseeing agriculture and technological education.Based on the sonar-camera sensor,an autonomous navigation system of the harvesting robot was built to move along the trough lines independently.The mature fruits were recognized according to the H(Hue)and S(Saturation)color feature and the picking-point were located by the binocular-vision unit.A nondestructive end-effector,used to suck the fruit,hold and cut the fruit-stem,was designed to prevent pericarp damage and disease infection.A joint-type industrial manipulator with six degrees-of-freedom(DOF)was utilized to carry the end-effector.The key points and time steps for the collision-free and rapid motion of manipulator were planned.Experimental results showed that all the 100 mature strawberry targets were recognized automatically in the harvesting test.The success harvesting rate was 86%,and the success harvesting operation cost 31.3 seconds on average,including a single harvest operation of 10 seconds.The average error for fruit location was less than 4.6 mm.展开更多
A tomato harvesting robot was developed in this study,which consisted of a four-wheel independent steering system,a 5-DOF harvesting system,a navigation system,and a binocular stereo vision system.The four-wheel indep...A tomato harvesting robot was developed in this study,which consisted of a four-wheel independent steering system,a 5-DOF harvesting system,a navigation system,and a binocular stereo vision system.The four-wheel independent steering system was capable of providing a low-speed steering control of the robot based on Ackerman steering geometry.The proportional-integral-derivative(PID)algorithm was used in the laser navigation control system.The Otsu algorithm and the elliptic template method were used for the automatic recognition of ripe tomatoes,and obstacle avoidance strategies were proposed based on the C-space method.The maximum average absolute error between the set angle and the actual angle was about 0.14°,and the maximum standard deviation was about 0.04°.The laser navigation system was able to rapidly and accurately track the path,with the deviation being less than 8 cm.The load bearing capacity of the mechanical arm was about 1.5 kg.The success rate of the binocular vision system in the recognition of ripe tomatoes was 99.3%.When the distance was less than 600 mm,the positioning error was less than 10 mm.The time needed for recognition of ripe tomatoes and pitching was about 15 s per tomato,with a success rate of about 86%.This study provides some insights into the development and application of tomato harvesting robot used in the greenhouse.展开更多
In order to reduce cucumber harvesting cost and improve economic benefits,a cucumber harvesting robot was developed.The cucumber harvesting robot consists of a vehicle,a 4-DOF articulated manipulator,an end-effector,a...In order to reduce cucumber harvesting cost and improve economic benefits,a cucumber harvesting robot was developed.The cucumber harvesting robot consists of a vehicle,a 4-DOF articulated manipulator,an end-effector,an upper monitor,a vision system and four DC servo drive systems.The Kinematics of the cucumber harvesting robot manipulator was constructed using D-H coordinate frame model.And the inverse kinematics which provides a foundation for trajectory planning has been solved with inverse transform technique.The cycloidal motion,which has properties of continuity and zero velocity and acceleration at the ports of the bounded interval,was adopted as a feasible approach to plan trajectory in joint space of the cucumber harvesting robot manipulator.Moreover,hardware and software based on CAN-bus communication between the upper monitor and the joint controllers have been designed.Experimental results show that the upper monitor communicates with the four joint controllers efficiently by CAN-bus,and the integrated errors of four joint angles do not exceed four degrees.Probable factors resulting in the errors were analyzed and the corresponding solutions for improving precision are proposed.展开更多
Due to the low working efficiency of apple harvesting robots,there is still a long way to go for commercialization.The machine performance and extended operating time are the two research aspects for improving efficie...Due to the low working efficiency of apple harvesting robots,there is still a long way to go for commercialization.The machine performance and extended operating time are the two research aspects for improving efficiencies of harvesting robots,this study focused on the extended operating time and proposed a round-the-clock operation mode.Due to the influences of light,temperature,humidity,etc.,the working environment at night is relatively complex,and thus restricts the operating efficiency of the apple harvesting robot.Three different artificial light sources(incandescent lamp,fluorescent lamp,and LED lights)were selected for auxiliary light according to certain rules so that the apple night vision images could be captured.In addition,by color analysis,night and natural light images were compared to find out the color characteristics of the night vision images,and intuitive visual and difference image methods were used to analyze the noise characteristics.The results showed that the incandescent lamp is the best artificial auxiliary light for apple harvesting robots working at night,and the type of noise contained in apple night vision images is Gaussian noise mixed with some salt and pepper noise.The preprocessing method can provide a theoretical and technical reference for subsequent image processing.展开更多
Automated harvesting of oil palm trees requires research and development efforts in several robotics areas,including manipulator control.The objective of this paper was to apply nonlinear Lyapunov based control method...Automated harvesting of oil palm trees requires research and development efforts in several robotics areas,including manipulator control.The objective of this paper was to apply nonlinear Lyapunov based control method for joint angles tracking of a two-link oil palm harvesting robot manipulator with uncertain system parameters.Four different controllers,including exact model knowledge,adaptive,sliding mode control and high gain feedback control were proposed and simulated.Stability analyses were performed for each case in the absence and presence of bounded disturbance.The controllers were then compared against each other based on their performances and control efforts.展开更多
Over the past 30 years,there has been continuous progress in global science and technology.However,many agricultural products still heavily rely on traditional methods of manual and mechanical harvesting,facing challe...Over the past 30 years,there has been continuous progress in global science and technology.However,many agricultural products still heavily rely on traditional methods of manual and mechanical harvesting,facing challenges such as high costs and low efficiency.To address these challenges,researchers have developed various harvesting robots to handle diverse tasks in complex farm environments.This study analyzed pertinent papers on harvesting robots retrieved from the Web of Science(WOS)core database and the China National Knowledge Infrastructure(CNKI)database,spanning the years 1993 to 2022.Using specialized software such as CiteSpace and VOSviewer,a bibliometric analysis was conducted to examine the research progress and hotspots in the field of harvesting robots.The analysis of 517 English papers indicated a continuous expansion in the research scale of harvesting robots.Furthermore,the research history can be divided into three distinct periods.Currently,research on harvesting robots is experiencing a rapid growth phase,with the number of related papers steadily increasing each year.In the year 2022 alone,151 English papers were published.This growth is attributed to close collaborations among different countries/regions,institutions,and authors.China,the United States,and Japan play crucial roles in the research of harvesting robots.Notably,China has published 326 English papers,ranking first globally.Through analysis,it was also found that Chinese papers focused on harvesting robots earlier,thereby promoting the development of agricultural robots.Additionally,bibliometric analysis revealed that the research hotspots of harvesting robots mainly include system and structure design,object recognition and localization,and multi-robot coordination,among others.In the future,development trends of harvesting robots will focus on:1)diversifying robot types,2)expanding application scenarios,3)enhancing overall performance to reduce losses,and 4)reducing manufacturing costs.In conclusion,through a comprehensive bibliometric analysis,this study has provided valuable insights to advance the automation of harvesting.展开更多
High harvesting success rate is part of the key technologies for robotic cherry tomato harvesting,which is closely related to the structural design of the end-effector.To obtain a high success rate of fruit harvesting...High harvesting success rate is part of the key technologies for robotic cherry tomato harvesting,which is closely related to the structural design of the end-effector.To obtain a high success rate of fruit harvesting,this paper presents a compliant end-effector with bio-inspired tarsus compliant gripper inspired by the structure and mechanics of the tarsal chain in the Serica orientalis Motschulsky.Response Surface Methodology(RSM)based on Box Behnken Design(BBD)technique has been used to optimize the key structural parameters of the bionic compliant end-effector for achieving the expected results in pulling pattern for robotic cherry tomato harvesting.Experiments were designed by maintaining three levels of four process parameters—Length of the Offset Segment Tarsomere(OSTL),Angle of the Inclined Segment Tarsomere(ISTA),Thickness of the Extended Segment Tarsomere(ESTT)and Length of the Extended Segment Tarsomere(ESTL).According to the optimization analysis results,the best parameter combination is OSTL 23 mm,ISTA 14°,ESTT 5.0 mm,ESTL 23 mm.Besides,the harvesting performance of the optimized bionic compliant end-effector was verified by experiments.The results indicated the harvesting success rate of fruits with different equatorial diameters was not less than 76%.展开更多
To address the limitation of low harvesting efficiency in intelligent mechanized harvesting in standardized orchards,a negative pressure adsorption apple harvesting robot has been designed and developed.The robot is b...To address the limitation of low harvesting efficiency in intelligent mechanized harvesting in standardized orchards,a negative pressure adsorption apple harvesting robot has been designed and developed.The robot is based on a Cartesian coordinate system and incorporates direct negative pressure adsorption picking combined with multi-stage buffering collection methods.Additionally,the proposed model pipeline integrates YOLOv8 and Segment Anything Model for precise apple picking point localization.Finally,field trials of the apple harvesting robot were conducted in a V-shaped layout apple orchard at Experiment and Demonstration Orchard at Tianping Lake.The experimental results showed an apple recognition rate of 90.54%,an overall harvesting success rate of 83.65%,an average picking efficiency of 4.83 s per fruit,and a damage rate of 13.61%.It demonstrates the potential of the robot in improving the efficiency and reliability of automated apple harvesting.At the same time,the results highlight the need to focus on enhancing the robustness of apple recognition algorithms under varying lighting conditions,and reducing apple damage rates by shortening the transport pipeline and optimizing the structure of the collection device.This study provides a promising solution for addressing global challenges in agricultural automation,offering insights into the future optimization of intelligent harvesting technologies.展开更多
Tomato picking is a time-consuming and laborious work.The use of intelligent equipment of picking instead of manual picking can improve the production efficiency.The end-effector is an important element in direct cont...Tomato picking is a time-consuming and laborious work.The use of intelligent equipment of picking instead of manual picking can improve the production efficiency.The end-effector is an important element in direct contact with tomato fruit,and it is the key to realize automatic tomato harvest.This paper introduces a rigid-flexible coupling end-effector with a telescopic pneumatic sucker.The end-effector first extends the vacuum sucker of the adhesion mechanism to hold the target tomato and pull it out for a certain distance,and then grips the tomato with a clamping component.The target tomato picking operation was completed through the movement mode of spiral and pull combination.The physical characteristics of tomato and the mechanical characteristics of fruit stem were investigated,aiming at providing a solid theoretical basis for the design and mechanical analysis of end-effector.Then,the stability of suction and pulling force in the process of holding and pulling tomato were analyzed,so as to clarify the specifications of suction and picking parts.Finally,a composite force analysis of the adhesion mechanism and the holding mechanism was undertaken to achieve the mechanical design goal of the tomato adhesion and picking movement process.The picking performance test of the end-effector showed that the picking time of single fruit was about 5.4s and the success rate of picking could reach 88%.This study provides sufficient theoretical basis for the development of tomato picking robot and the design of end-effector.展开更多
Harvesting of fresh-eating cherry tomato was highly costly on labor and time.In order to achieve mechanical harvesting for the fresh-eating tomato,a new harvesting robot was designed,which consisted of a stereo visual...Harvesting of fresh-eating cherry tomato was highly costly on labor and time.In order to achieve mechanical harvesting for the fresh-eating tomato,a new harvesting robot was designed,which consisted of a stereo visual unit,an end-effector,manipulator,a fruit collector,and a railed vehicle.The robot configuration and workflow design focused on the special cultivating condition.Three key parts were introduced in detail:a railroad vehicle capably moving on both ground and rail was adopted as the robot’s carrier,a visual servo unit was used to identify and locate the mature fruits bunch,and the end-effector to hold and separate the fruit bunch was designed based on the stalk’s mechanical features.The field test of the new developed robot was conducted and the results were analyzed.The successful harvest rate of the robot was 83%,however,each successful harvest averagely needed 1.4 times attempt,and a single successful harvesting cycle cost 8 s excluding the time cost on moving.展开更多
To realize the robotic harvesting of Hangzhou White Chrysanthemums,the quick recognition and 3D vision localization system for target Chrysanthemums was investigated in this study.The system was comprised of three mai...To realize the robotic harvesting of Hangzhou White Chrysanthemums,the quick recognition and 3D vision localization system for target Chrysanthemums was investigated in this study.The system was comprised of three main stages.Firstly,an end-effector and a simple freedom manipulator with three degrees were designed to meet the quality requirements of harvesting Hangzhou White Chrysanthemums.Secondly,a segmentation based on HSV color space was performed.A fast Fuzzy C-means(FCM)algorithm based on S component was proposed to extract the target image from irrelevant background.Thirdly,binocular stereo vision was used to acquire the target spatial information.According to the shape of Hangzhou White Chrysanthemums,the centroids of stamens were selected as feature points to match in the right and left images.The experimental results showed that the proposed method was able to recognize Hangzhou White Chrysanthemums with the accuracy of 85%.When the distance between target and baseline was 150-450 mm,the errors between the calculated and measured distance were less than 14 mm,which could meet the requirements of the localization accuracy of the harvesting robot.展开更多
Banana de-handing is an important part of banana post-harvesting operation.The traditional artificial de-handing model has problems such as labor intensity,inaccurate cutting,uneven cutting surface,unstable catching,a...Banana de-handing is an important part of banana post-harvesting operation.The traditional artificial de-handing model has problems such as labor intensity,inaccurate cutting,uneven cutting surface,unstable catching,and damage of banana fruit,etc.The mapping relationship between the characteristic parameters of the movement posture of the cutter and the influencing factors of the contact stress of banana crown cutting in unstructured environments,and the changing rules of the bumping contact stress of complex multi-shaped banana fruit with the physical property parameters of the cushioning material are the theoretical and technical difficulties that urgently need to be solved in the realization of banana mechanical de-handing.The future research(research on the coupling mechanism of visual cognition-mechanism cutting and low-destructive catching method of full-field continuous de-handing of bananas under multi-constraint scenarios)should:(1)create a database of banana crown,obtain the optimal banana crown recognition model,develop a recognition and locating system of the cutting line of banana crown and obtain its spatial location information;(2)establish the discrete element mechanical model of banana crown and the interaction model between banana crown and the cutter,clarify the stress change and the force wave transmission characteristics of the cutting process,construct the multi-objective optimization equation of the cutting performance,obtain the best combination of cutting parameters,and ascertain the mechanisms of synergistic locating and continuous cutting of banana crown;(3)establish the contact mechanical model of banana fruit drop-bump,parse the bumping characteristics between banana fruit and cushioning material,construct mathematical equations to quantitatively assess damage results,and determine the detract catching method of banana fruit that matches the de-handing mode in multi-constraint scenarios.This study showed that the real-time identification and spatial positioning of fruit,the mechanical properties of crown and the optimization of cutting performance,the damage mechanism of fruit and its loss-reducing harvesting method are the three key breakthroughs in realizing the robotization of de-handing.The current bottleneck problems and future research directions of intelligent banana de-handing were pointed out in this paper,which can provide a theoretical basis for the optimal design of banana de-handing devices and provide technical support for promoting the practical application of intelligent de-handing equipment.展开更多
The harvesting of fresh kiwifruit is a labor-intensive operation that accounts for more than 25%of annual production costs.Mechanized harvesting technologies are thus being developed to reduce labor requirements for h...The harvesting of fresh kiwifruit is a labor-intensive operation that accounts for more than 25%of annual production costs.Mechanized harvesting technologies are thus being developed to reduce labor requirements for harvesting kiwifruit.To improve the efficiency of a harvesting robot for picking kiwifruit,we designed an end-effector,which we report herein along with the results of tests to verify its operation.By using the established method of automated picking discussed in the literature and which is based on the characteristics of kiwifruit,we propose an automated method to pick kiwifruit that consists of separating the fruit from its stem on the tree.This method is experimentally verified by using it to pick clustered kiwifruit in a scaffolding canopy cultivation.In the experiment,the end-effector approaches a fruit from below and then envelops and grabs it with two bionic fingers.The fingers are then bent to separate the fruit from its stem.The grabbing,picking,and unloading processes are integrated,with automated picking and unloading performed using a connecting rod linkage following a trajectory model.The trajectory was analyzed and validated by using a simulation implemented in the software Automatic Dynamic Analysis of Mechanical Systems(ADAMS).In addition,a prototype of an end-effector was constructed,and its bionic fingers were equipped with fiber sensors to detect the best position for grabbing the kiwifruit and pressure sensors to ensure that the damage threshold was respected while picking.Tolerances for size and shape were incorporated by following a trajectory groove from grabbing and picking to unloading.The end-effector separates clustered kiwifruit and automatically grabs individual fruits.It takes on average 4–5 s to pick a single fruit,with a successful picking rate of 94.2%in an orchard test featuring 240 samples.This study shows the grabbing–picking–unloading robotic end-effector has significant potential to facilitate the harvesting of kiwifruit.展开更多
The end-effector is an important part of the broccoli harvesting robot.Aiming at the physical characteristics of a large broccoli head and thick stem,a spherical cutting tool broccoli harvesting end-effector was desig...The end-effector is an important part of the broccoli harvesting robot.Aiming at the physical characteristics of a large broccoli head and thick stem,a spherical cutting tool broccoli harvesting end-effector was designed in this study.First,the physical characteristics of broccoli were tested,and physical parameters such as the broccoli head diameter and stem diameter of broccoli were measured.The maximum cutting force of broccoli stems under different cutting angles was tested.Second,according to the physical characteristics and harvesting process of broccoli,the end-effector was designed,and the mathematical model of kinematics and dynamics was established.Based on the results of dynamic analysis,the end-effector rod was optimized,and the unilateral width of the slider was 40 mm,the length of the connecting rod was 120 mm,and the length of the crank was 42 mm.The mechanism needed an external driving force of 140.54 N to cut the broccoli stem.Therefore,a 32 mm cylinder with a load rate of 50%was selected as the power source.Finally,the feasibility of the broccoli harvesting end-effector was verified by the harvesting test.Experiments showed that the overall harvesting success rate of the end-effector is 93.3%,and the smoothness rate of the stem section is 83.3%.The harvesting performance of the broccoli end-effector was verified.This lays a foundation for agricultural robots to harvest broccoli.展开更多
Soft robotics,often taking inspirations from biomimetics,is an exciting novel research field and has great capability to work with creatures.A new type of bio-soft robot inspired by elephant trunk and octopus was prop...Soft robotics,often taking inspirations from biomimetics,is an exciting novel research field and has great capability to work with creatures.A new type of bio-soft robot inspired by elephant trunk and octopus was proposed,which has a promising application in robotic agricultural harvesting.The two modularized structures,basal segment and caudal segment,were elaborated in detail.They both have three side chambers and one central chamber,which are reinforced by springs for better stretch performance in axial direction without radial expansion.All the chambers can act as drivers when inflated with compressed air.More importantly,the central chamber was designed for regulating the stiffness of the robot module as needed in application.The primary static model for axial elongation was established for the fundamental analysis of the bio-soft robot module’s features,such as iso-force,isobaric and isometric characteristics.Simulation and experimental results showed that the motion of the proposed bio-soft module has approximate linearity in iso-force and isobaric conditions,and strict linearity in isometric condition.展开更多
In response to the prevailing scarcity of labor and with the aim of augmenting the proportion of premium-quality fruits, a robotic grading end-effector system for harvesting was meticulously designed. The end-effector...In response to the prevailing scarcity of labor and with the aim of augmenting the proportion of premium-quality fruits, a robotic grading end-effector system for harvesting was meticulously designed. The end-effector could measure the soluble solid content (SSC) of peaches during the harvesting process to evaluate the quality of the fruit, thereby facilitating real-time grading during harvesting. As comprising a harvesting component and an information-gathering segment, the end-effector system was optimized with the primary structural parameters of its adaptive fingers using a mathematical model of peach morphology. Also, the buffering materials for mitigating the pressure exerted by the adaptive fingers on the peaches were compared. Furthermore, feasibility analyses of the grasping actions were conducted based on the interaction forces between the adaptive fingers and the peaches. To grade the quality of peaches, SSC was used as an indicator to assess and grade the quality of the peaches. The spectra of peaches within the wavelength range of 590-1100 nm were collected, and a predictive model for SSC was developed. The correlation coefficients for the calibration set and prediction sets of the predictive model were 0.880 and 0.890, with corresponding root mean square errors of 0.370% and 0.357% Brix, respectively. In addition, a robustness and accuracy assessment was conducted using 30 peach samples, yielding a correlation coefficient of 0.936 and a standard error of 0.386% Brix between the predicted and measured values of SSC. The results confirm that the end-effector can measure the SSC of peaches during the collection process, providing novel concepts and theoretical foundations for real-time harvesting and grading.展开更多
基金supported by the Key R&D Projects in the Artificial Intelligence Pilot Area of Chongqing,China(cstc2021jscxgksbX0067)the Fundamental Research Funds for the Central Universities(SWU-KT22024)the Local Financial of National Agricultural Science&Technology Center,Chengdu(NASC2021KR02)。
文摘In response to the demand of automatic fruit identification and harvesting,this paper presents a human-robot collaborative picking robot based on somatosensory interactive servo control.The robot system mainly consisted of four parts:picking execution mechanism,hand information acquisition system,human-machine interaction interface,and human-robot collaborative picking strategy.A six-degree-of-freedom robotic arm was designed as the picking execution mechanism.The D-H method is employed for both forward and inverse kinematic modeling of the robotic arm.A four-step inverse kinematic optimal solution selection method,including mechanical interference,correctness,rationality,and smoothness of motion,is proposed.The working principle and use of the Leap Motion controller for hand information acquisition were introduced.Data from three types of hand movements were collected and analyzed.Spatial mapping method between the Leap Motion interaction space and operating range of the robotic arm was proposed to achieve a direct correspondence between the cubic interaction box and the cylindrical space of the fan ring of the robotic arm.The test results demonstrated that the average response time of the double-click picking command was 332 ms.The average time consumption for somatosensory control targeting was 6.5 s.The accuracy rate of the picking gesture judgment was 96.7%.
基金support from the National Key Research and Development Program of China(Grant No.2022YFD2000500).
文摘In greenhouse environments,using automated machines for tomato harvesting to reduce labor consumption is a future development trend.Accurate and effective visual recognition is essential to accomplish harvesting tasks.However,most current studies use various models to gain harvesting information in multiple steps,resulting in heavy calculation costs,poor real-time availability,and weak recognition precision.In this study,an improved YOLOv8np-RCW end-to-end model based on YOLOv8n pose is proposed to simultaneously detect tomato bunches,maturity,and keypoints using a decoupled-head structure.The model integrates a ResNet-enhanced RepVGG architecture for a balance of accuracy and speed,employs the CARAFE upsampling algorithm for a larger receptive field with lightweight design,and optimizes the loss function with WIoU loss to enhance bounding box prediction,maturity detection,and keypoint extraction.Experimental results indicate that mAP50 of YOLOv8np-RCW model for bounding box and keypoints is 87.3%and 86.8%respectively,which is 6.2%and 5.5%higher than YOLOv8n pose model.Completing the tasks of bunch detection,maturity assessment,and keypoint localization requires only 9.8 ms.Euclidean distance error is less than 20 pixels in detecting keypoints.Based on this model,a method is proposed to quickly determine the orientation of tomato bunches using geometric cross-product and cross-multiplication calculations from keypoint 2D information,providing guidance for the motion planning of the end-effector.In field experiments,the robot achieved a harvesting success rate of 68%,with an average time of 10.8366 seconds per tomato bunch.
基金the National High Technology Research and Development Program of China(2013AA100307)。
文摘In order to improve the operating precision of the harvesting robot,a vision system for intelligently identifying and locating the mature tomato was designed.The active detection method based on structured-light stereo vision was expected to deal with the problem of variable illumination and target occlusion in the glasshouse.The maximum between-cluster variances of hue(H)and saturation(S)value were adopted as the threshold for color segmentation,which weakened the impact on the image caused by the light intensity variation.Through the limit on the pixel size and circularity of the candidate areas,the vision system recognized the fruit area and removed the noise areas.The fruit’s 3D position was computed on the basis of spatial relationship between the laser plane and the camera,when the linear laser was projected on the centre area of the mature fruit.The blue view-scanning laser stripe pixels on the mature fruit were extracted according to its Cb color characteristic.As the field test results show,the measurement error on the fruit radius is less than 5 mm,the centre distance error between the fruit and camera is less than 7 mm,and the single axis coordinate error is less than 5.6 mm.This structured-light vision system could effectively identify and locate mature fruit.
基金International Science&Technology Cooperation Program of China(2013DFA11470)the National Natural Science Foundation of China(30771243)+1 种基金International Science&Technology Cooperation Program of Chongqing(cstc2011gjhz80001)Fundamental Research Funds for the Central Universities(XDJK2013C102).
文摘With the decrease of agricultural labor and the increase of production cost,the researches on citrus harvesting robot(CHR)have received more and more attention in recent years.For the success of robotic harvesting and the safety of robot,the identification of mature citrus fruit and obstacle is the priority of robotic harvesting.In this work,a machine vision system,which consisted of a color CCD camera and a computer,was developed to achieve these tasks.Images of citrus trees were captured under sunny and cloudy conditions.Due to varying degrees of lightness and position randomness of fruits and branches,red,green,and blue values of objects in these images are changed dramatically.The traditional threshold segmentation is not efficient to solve these problems.Multi-class support vector machine(SVM),which succeeds by morphological operation,was used to simultaneously segment the fruits and branches in this study.The recognition rate of citrus fruit was 92.4%,and the branch of which diameter was more than 5 pixels,could be recognized.The results showed that the algorithm could be used to detect the fruits and branches for CHR.
基金Funding for this research was provided by the National High Technology Research and Development Program of China(2012AA101903)the National Science&Technology Pillar Program of China(2012BAF07B02).
文摘In order to improve robotic harvesting and reduce production cost,a harvesting robot system for strawberry on the elevated-trough culture was designed.It was supposed to serve for sightseeing agriculture and technological education.Based on the sonar-camera sensor,an autonomous navigation system of the harvesting robot was built to move along the trough lines independently.The mature fruits were recognized according to the H(Hue)and S(Saturation)color feature and the picking-point were located by the binocular-vision unit.A nondestructive end-effector,used to suck the fruit,hold and cut the fruit-stem,was designed to prevent pericarp damage and disease infection.A joint-type industrial manipulator with six degrees-of-freedom(DOF)was utilized to carry the end-effector.The key points and time steps for the collision-free and rapid motion of manipulator were planned.Experimental results showed that all the 100 mature strawberry targets were recognized automatically in the harvesting test.The success harvesting rate was 86%,and the success harvesting operation cost 31.3 seconds on average,including a single harvest operation of 10 seconds.The average error for fruit location was less than 4.6 mm.
基金supported by the National 863 planning project of China-digital design and intelligent control technology of agricultural facilities equipment(2013AA102406)the Beijing municipal science and technology project(Z161100004916118).
文摘A tomato harvesting robot was developed in this study,which consisted of a four-wheel independent steering system,a 5-DOF harvesting system,a navigation system,and a binocular stereo vision system.The four-wheel independent steering system was capable of providing a low-speed steering control of the robot based on Ackerman steering geometry.The proportional-integral-derivative(PID)algorithm was used in the laser navigation control system.The Otsu algorithm and the elliptic template method were used for the automatic recognition of ripe tomatoes,and obstacle avoidance strategies were proposed based on the C-space method.The maximum average absolute error between the set angle and the actual angle was about 0.14°,and the maximum standard deviation was about 0.04°.The laser navigation system was able to rapidly and accurately track the path,with the deviation being less than 8 cm.The load bearing capacity of the mechanical arm was about 1.5 kg.The success rate of the binocular vision system in the recognition of ripe tomatoes was 99.3%.When the distance was less than 600 mm,the positioning error was less than 10 mm.The time needed for recognition of ripe tomatoes and pitching was about 15 s per tomato,with a success rate of about 86%.This study provides some insights into the development and application of tomato harvesting robot used in the greenhouse.
基金the Natural Science Foundation of China(50575206)the National High-Tech Research and Development(863)Program of China(2007AA04Z222)。
文摘In order to reduce cucumber harvesting cost and improve economic benefits,a cucumber harvesting robot was developed.The cucumber harvesting robot consists of a vehicle,a 4-DOF articulated manipulator,an end-effector,an upper monitor,a vision system and four DC servo drive systems.The Kinematics of the cucumber harvesting robot manipulator was constructed using D-H coordinate frame model.And the inverse kinematics which provides a foundation for trajectory planning has been solved with inverse transform technique.The cycloidal motion,which has properties of continuity and zero velocity and acceleration at the ports of the bounded interval,was adopted as a feasible approach to plan trajectory in joint space of the cucumber harvesting robot manipulator.Moreover,hardware and software based on CAN-bus communication between the upper monitor and the joint controllers have been designed.Experimental results show that the upper monitor communicates with the four joint controllers efficiently by CAN-bus,and the integrated errors of four joint angles do not exceed four degrees.Probable factors resulting in the errors were analyzed and the corresponding solutions for improving precision are proposed.
基金supported by the Natural Science Foundation of Shandong Province in China(ZR2017BC013,ZR2014FM001)National Nature Science Foundation of China(No.31571571,61572300)+1 种基金Taishan Scholar Program of Shandong Province of China(No.TSHW201502038)Priority Academic Program Development of Jiangsu Higher Education Institutions.
文摘Due to the low working efficiency of apple harvesting robots,there is still a long way to go for commercialization.The machine performance and extended operating time are the two research aspects for improving efficiencies of harvesting robots,this study focused on the extended operating time and proposed a round-the-clock operation mode.Due to the influences of light,temperature,humidity,etc.,the working environment at night is relatively complex,and thus restricts the operating efficiency of the apple harvesting robot.Three different artificial light sources(incandescent lamp,fluorescent lamp,and LED lights)were selected for auxiliary light according to certain rules so that the apple night vision images could be captured.In addition,by color analysis,night and natural light images were compared to find out the color characteristics of the night vision images,and intuitive visual and difference image methods were used to analyze the noise characteristics.The results showed that the incandescent lamp is the best artificial auxiliary light for apple harvesting robots working at night,and the type of noise contained in apple night vision images is Gaussian noise mixed with some salt and pepper noise.The preprocessing method can provide a theoretical and technical reference for subsequent image processing.
文摘Automated harvesting of oil palm trees requires research and development efforts in several robotics areas,including manipulator control.The objective of this paper was to apply nonlinear Lyapunov based control method for joint angles tracking of a two-link oil palm harvesting robot manipulator with uncertain system parameters.Four different controllers,including exact model knowledge,adaptive,sliding mode control and high gain feedback control were proposed and simulated.Stability analyses were performed for each case in the absence and presence of bounded disturbance.The controllers were then compared against each other based on their performances and control efforts.
基金financially supported by the Qinchuangyuan Project of Shaanxi Province(Grant No.2023KXJ-016)the National Natural Science Foundation of China(Grant No.32272001)the Shaanxi Key Research and Development Project(Grant No.2023-ZDLNY-62 and No.2022NY-205).
文摘Over the past 30 years,there has been continuous progress in global science and technology.However,many agricultural products still heavily rely on traditional methods of manual and mechanical harvesting,facing challenges such as high costs and low efficiency.To address these challenges,researchers have developed various harvesting robots to handle diverse tasks in complex farm environments.This study analyzed pertinent papers on harvesting robots retrieved from the Web of Science(WOS)core database and the China National Knowledge Infrastructure(CNKI)database,spanning the years 1993 to 2022.Using specialized software such as CiteSpace and VOSviewer,a bibliometric analysis was conducted to examine the research progress and hotspots in the field of harvesting robots.The analysis of 517 English papers indicated a continuous expansion in the research scale of harvesting robots.Furthermore,the research history can be divided into three distinct periods.Currently,research on harvesting robots is experiencing a rapid growth phase,with the number of related papers steadily increasing each year.In the year 2022 alone,151 English papers were published.This growth is attributed to close collaborations among different countries/regions,institutions,and authors.China,the United States,and Japan play crucial roles in the research of harvesting robots.Notably,China has published 326 English papers,ranking first globally.Through analysis,it was also found that Chinese papers focused on harvesting robots earlier,thereby promoting the development of agricultural robots.Additionally,bibliometric analysis revealed that the research hotspots of harvesting robots mainly include system and structure design,object recognition and localization,and multi-robot coordination,among others.In the future,development trends of harvesting robots will focus on:1)diversifying robot types,2)expanding application scenarios,3)enhancing overall performance to reduce losses,and 4)reducing manufacturing costs.In conclusion,through a comprehensive bibliometric analysis,this study has provided valuable insights to advance the automation of harvesting.
基金This work was supported by Anhui Provincial Major Science and Technology Project(Project No.202203a06020002)the Fundamental Research Funds for the Central Universities(No.BC210202084).
文摘High harvesting success rate is part of the key technologies for robotic cherry tomato harvesting,which is closely related to the structural design of the end-effector.To obtain a high success rate of fruit harvesting,this paper presents a compliant end-effector with bio-inspired tarsus compliant gripper inspired by the structure and mechanics of the tarsal chain in the Serica orientalis Motschulsky.Response Surface Methodology(RSM)based on Box Behnken Design(BBD)technique has been used to optimize the key structural parameters of the bionic compliant end-effector for achieving the expected results in pulling pattern for robotic cherry tomato harvesting.Experiments were designed by maintaining three levels of four process parameters—Length of the Offset Segment Tarsomere(OSTL),Angle of the Inclined Segment Tarsomere(ISTA),Thickness of the Extended Segment Tarsomere(ESTT)and Length of the Extended Segment Tarsomere(ESTL).According to the optimization analysis results,the best parameter combination is OSTL 23 mm,ISTA 14°,ESTT 5.0 mm,ESTL 23 mm.Besides,the harvesting performance of the optimized bionic compliant end-effector was verified by experiments.The results indicated the harvesting success rate of fruits with different equatorial diameters was not less than 76%.
基金supported by China’s Central Guiding Local Technology Development Special Fund Project(Grant No.ZYYD2025CG21)the Zhejiang Science and Technology Plan Project-National Key Research and Development Program of China(Grant No.2019C03075)+1 种基金“Leading Goose”Research and Development Program Subproject of Zhejiang(Grant No.2022C02021)Xinjiang Boshiran Intelligent Agricultural Machinery Co.,Ltd.(Grant No.KYY-HX-20210639).
文摘To address the limitation of low harvesting efficiency in intelligent mechanized harvesting in standardized orchards,a negative pressure adsorption apple harvesting robot has been designed and developed.The robot is based on a Cartesian coordinate system and incorporates direct negative pressure adsorption picking combined with multi-stage buffering collection methods.Additionally,the proposed model pipeline integrates YOLOv8 and Segment Anything Model for precise apple picking point localization.Finally,field trials of the apple harvesting robot were conducted in a V-shaped layout apple orchard at Experiment and Demonstration Orchard at Tianping Lake.The experimental results showed an apple recognition rate of 90.54%,an overall harvesting success rate of 83.65%,an average picking efficiency of 4.83 s per fruit,and a damage rate of 13.61%.It demonstrates the potential of the robot in improving the efficiency and reliability of automated apple harvesting.At the same time,the results highlight the need to focus on enhancing the robustness of apple recognition algorithms under varying lighting conditions,and reducing apple damage rates by shortening the transport pipeline and optimizing the structure of the collection device.This study provides a promising solution for addressing global challenges in agricultural automation,offering insights into the future optimization of intelligent harvesting technologies.
基金supported by the 2023 Open Project of Key Laboratory of Modern Agricultural Equipment and Technology(Jiangsu University),Ministry of Education and High-tech Key Laboratory of Agricultural Equipment and Intelligence of Jiangsu Province of China(MAET202319 and MAET 202327)the Key Agricultural Science and Technological Independent Innovation Fund of Jiangsu Province of China(CX(24)3032 and CX(21)1007).
文摘Tomato picking is a time-consuming and laborious work.The use of intelligent equipment of picking instead of manual picking can improve the production efficiency.The end-effector is an important element in direct contact with tomato fruit,and it is the key to realize automatic tomato harvest.This paper introduces a rigid-flexible coupling end-effector with a telescopic pneumatic sucker.The end-effector first extends the vacuum sucker of the adhesion mechanism to hold the target tomato and pull it out for a certain distance,and then grips the tomato with a clamping component.The target tomato picking operation was completed through the movement mode of spiral and pull combination.The physical characteristics of tomato and the mechanical characteristics of fruit stem were investigated,aiming at providing a solid theoretical basis for the design and mechanical analysis of end-effector.Then,the stability of suction and pulling force in the process of holding and pulling tomato were analyzed,so as to clarify the specifications of suction and picking parts.Finally,a composite force analysis of the adhesion mechanism and the holding mechanism was undertaken to achieve the mechanical design goal of the tomato adhesion and picking movement process.The picking performance test of the end-effector showed that the picking time of single fruit was about 5.4s and the success rate of picking could reach 88%.This study provides sufficient theoretical basis for the development of tomato picking robot and the design of end-effector.
基金We acknowledge that this work was financially supported by the National Natural Science Foundation of China(61703048)Beijing Excellent Talent Training to Support Young Key Individual Projects(2015000020060G134)BAAFS Youth Research Fund(QNJJ201722).
文摘Harvesting of fresh-eating cherry tomato was highly costly on labor and time.In order to achieve mechanical harvesting for the fresh-eating tomato,a new harvesting robot was designed,which consisted of a stereo visual unit,an end-effector,manipulator,a fruit collector,and a railed vehicle.The robot configuration and workflow design focused on the special cultivating condition.Three key parts were introduced in detail:a railroad vehicle capably moving on both ground and rail was adopted as the robot’s carrier,a visual servo unit was used to identify and locate the mature fruits bunch,and the end-effector to hold and separate the fruit bunch was designed based on the stalk’s mechanical features.The field test of the new developed robot was conducted and the results were analyzed.The successful harvest rate of the robot was 83%,however,each successful harvest averagely needed 1.4 times attempt,and a single successful harvesting cycle cost 8 s excluding the time cost on moving.
基金This work was financially supported by the project of National Science and Technology Supporting Plan(2015BAF01B02)the Open Foundation of Intelligent Robots and Systems at the University of Beijing Institute of Technology,High-tech Innovation Center(2016IRS03).
文摘To realize the robotic harvesting of Hangzhou White Chrysanthemums,the quick recognition and 3D vision localization system for target Chrysanthemums was investigated in this study.The system was comprised of three main stages.Firstly,an end-effector and a simple freedom manipulator with three degrees were designed to meet the quality requirements of harvesting Hangzhou White Chrysanthemums.Secondly,a segmentation based on HSV color space was performed.A fast Fuzzy C-means(FCM)algorithm based on S component was proposed to extract the target image from irrelevant background.Thirdly,binocular stereo vision was used to acquire the target spatial information.According to the shape of Hangzhou White Chrysanthemums,the centroids of stamens were selected as feature points to match in the right and left images.The experimental results showed that the proposed method was able to recognize Hangzhou White Chrysanthemums with the accuracy of 85%.When the distance between target and baseline was 150-450 mm,the errors between the calculated and measured distance were less than 14 mm,which could meet the requirements of the localization accuracy of the harvesting robot.
基金supported by the National Natural Science Foundation of China(32271996)Zhejiang Provincial Key R&D Program of China(2022C02013 and 2021C02023)+2 种基金Bingtuan Science and Technology Program(2021 DB001)Postdoctoral Fellowship Program of China Postdoctoral Science Foundation(GZC20232310)the China Scholarship Council.
文摘Banana de-handing is an important part of banana post-harvesting operation.The traditional artificial de-handing model has problems such as labor intensity,inaccurate cutting,uneven cutting surface,unstable catching,and damage of banana fruit,etc.The mapping relationship between the characteristic parameters of the movement posture of the cutter and the influencing factors of the contact stress of banana crown cutting in unstructured environments,and the changing rules of the bumping contact stress of complex multi-shaped banana fruit with the physical property parameters of the cushioning material are the theoretical and technical difficulties that urgently need to be solved in the realization of banana mechanical de-handing.The future research(research on the coupling mechanism of visual cognition-mechanism cutting and low-destructive catching method of full-field continuous de-handing of bananas under multi-constraint scenarios)should:(1)create a database of banana crown,obtain the optimal banana crown recognition model,develop a recognition and locating system of the cutting line of banana crown and obtain its spatial location information;(2)establish the discrete element mechanical model of banana crown and the interaction model between banana crown and the cutter,clarify the stress change and the force wave transmission characteristics of the cutting process,construct the multi-objective optimization equation of the cutting performance,obtain the best combination of cutting parameters,and ascertain the mechanisms of synergistic locating and continuous cutting of banana crown;(3)establish the contact mechanical model of banana fruit drop-bump,parse the bumping characteristics between banana fruit and cushioning material,construct mathematical equations to quantitatively assess damage results,and determine the detract catching method of banana fruit that matches the de-handing mode in multi-constraint scenarios.This study showed that the real-time identification and spatial positioning of fruit,the mechanical properties of crown and the optimization of cutting performance,the damage mechanism of fruit and its loss-reducing harvesting method are the three key breakthroughs in realizing the robotization of de-handing.The current bottleneck problems and future research directions of intelligent banana de-handing were pointed out in this paper,which can provide a theoretical basis for the optimal design of banana de-handing devices and provide technical support for promoting the practical application of intelligent de-handing equipment.
基金This research was conducted in the College of Mechanical and Electronic Engineering,Northwest A&F University,and was supported by research grants from the General Program of the National Natural Science Foundation of China(61175099).
文摘The harvesting of fresh kiwifruit is a labor-intensive operation that accounts for more than 25%of annual production costs.Mechanized harvesting technologies are thus being developed to reduce labor requirements for harvesting kiwifruit.To improve the efficiency of a harvesting robot for picking kiwifruit,we designed an end-effector,which we report herein along with the results of tests to verify its operation.By using the established method of automated picking discussed in the literature and which is based on the characteristics of kiwifruit,we propose an automated method to pick kiwifruit that consists of separating the fruit from its stem on the tree.This method is experimentally verified by using it to pick clustered kiwifruit in a scaffolding canopy cultivation.In the experiment,the end-effector approaches a fruit from below and then envelops and grabs it with two bionic fingers.The fingers are then bent to separate the fruit from its stem.The grabbing,picking,and unloading processes are integrated,with automated picking and unloading performed using a connecting rod linkage following a trajectory model.The trajectory was analyzed and validated by using a simulation implemented in the software Automatic Dynamic Analysis of Mechanical Systems(ADAMS).In addition,a prototype of an end-effector was constructed,and its bionic fingers were equipped with fiber sensors to detect the best position for grabbing the kiwifruit and pressure sensors to ensure that the damage threshold was respected while picking.Tolerances for size and shape were incorporated by following a trajectory groove from grabbing and picking to unloading.The end-effector separates clustered kiwifruit and automatically grabs individual fruits.It takes on average 4–5 s to pick a single fruit,with a successful picking rate of 94.2%in an orchard test featuring 240 samples.This study shows the grabbing–picking–unloading robotic end-effector has significant potential to facilitate the harvesting of kiwifruit.
基金the Key Research Projects of Zhejiang Province(Grant No.2022C02042,2022C02002)the National Natural Science Foundation of China(Grant No.32071909)+1 种基金the Shanghai Science and Technology Agricultural Development Project 2021(No.4-1)the General Project of Agriculture and Social Development in Hangzhou(Grant No.202203B08,20201203B92)。
文摘The end-effector is an important part of the broccoli harvesting robot.Aiming at the physical characteristics of a large broccoli head and thick stem,a spherical cutting tool broccoli harvesting end-effector was designed in this study.First,the physical characteristics of broccoli were tested,and physical parameters such as the broccoli head diameter and stem diameter of broccoli were measured.The maximum cutting force of broccoli stems under different cutting angles was tested.Second,according to the physical characteristics and harvesting process of broccoli,the end-effector was designed,and the mathematical model of kinematics and dynamics was established.Based on the results of dynamic analysis,the end-effector rod was optimized,and the unilateral width of the slider was 40 mm,the length of the connecting rod was 120 mm,and the length of the crank was 42 mm.The mechanism needed an external driving force of 140.54 N to cut the broccoli stem.Therefore,a 32 mm cylinder with a load rate of 50%was selected as the power source.Finally,the feasibility of the broccoli harvesting end-effector was verified by the harvesting test.Experiments showed that the overall harvesting success rate of the end-effector is 93.3%,and the smoothness rate of the stem section is 83.3%.The harvesting performance of the broccoli end-effector was verified.This lays a foundation for agricultural robots to harvest broccoli.
基金NSFC-Zhejiang Joint Foundation(Grant No.U1509212)National Natural Science Foundation of China(Grant No.51405441,51605434)Natural Science Foundation of Zhejiang Province(Grant No.Q15E050025).
文摘Soft robotics,often taking inspirations from biomimetics,is an exciting novel research field and has great capability to work with creatures.A new type of bio-soft robot inspired by elephant trunk and octopus was proposed,which has a promising application in robotic agricultural harvesting.The two modularized structures,basal segment and caudal segment,were elaborated in detail.They both have three side chambers and one central chamber,which are reinforced by springs for better stretch performance in axial direction without radial expansion.All the chambers can act as drivers when inflated with compressed air.More importantly,the central chamber was designed for regulating the stiffness of the robot module as needed in application.The primary static model for axial elongation was established for the fundamental analysis of the bio-soft robot module’s features,such as iso-force,isobaric and isometric characteristics.Simulation and experimental results showed that the motion of the proposed bio-soft module has approximate linearity in iso-force and isobaric conditions,and strict linearity in isometric condition.
基金supported by the National Natural Science Foundation of China (Grant No. U23A20175)the “Leading Goose” R&D Program of Zhejiang (Grant No. 2022C02052)+1 种基金the Scientific Research Fund of Zhejiang Provincial Education Department (Grant No. Y202250747)Wenzhou Science and Technology Commissioner Special Project (Grant No. X2023045).
文摘In response to the prevailing scarcity of labor and with the aim of augmenting the proportion of premium-quality fruits, a robotic grading end-effector system for harvesting was meticulously designed. The end-effector could measure the soluble solid content (SSC) of peaches during the harvesting process to evaluate the quality of the fruit, thereby facilitating real-time grading during harvesting. As comprising a harvesting component and an information-gathering segment, the end-effector system was optimized with the primary structural parameters of its adaptive fingers using a mathematical model of peach morphology. Also, the buffering materials for mitigating the pressure exerted by the adaptive fingers on the peaches were compared. Furthermore, feasibility analyses of the grasping actions were conducted based on the interaction forces between the adaptive fingers and the peaches. To grade the quality of peaches, SSC was used as an indicator to assess and grade the quality of the peaches. The spectra of peaches within the wavelength range of 590-1100 nm were collected, and a predictive model for SSC was developed. The correlation coefficients for the calibration set and prediction sets of the predictive model were 0.880 and 0.890, with corresponding root mean square errors of 0.370% and 0.357% Brix, respectively. In addition, a robustness and accuracy assessment was conducted using 30 peach samples, yielding a correlation coefficient of 0.936 and a standard error of 0.386% Brix between the predicted and measured values of SSC. The results confirm that the end-effector can measure the SSC of peaches during the collection process, providing novel concepts and theoretical foundations for real-time harvesting and grading.
